Data Science I

Course ID

Course Name

Instructor

Semester

Time | Day

HGEN 611

Data Science I

Timothy York

Fall

10:30-11:50 | WF

This course will introduce students to tools and techniques from the discipline of data science that support efficient and reproducible scientific computing. Students will gain hands-on experience developing complete data analysis projects based on real-world datasets. Lessons will cover the primary tasks that comprise most analyses: data management/acquisition, cleaning, reshaping, manipulation, analysis and visualization, as well as strategies for arranging these constituent parts into cohesive workflows that are verifiable, easily repeatable and consistent with best practices for reproducible computational research. This course will focus on the statistical programming language R but no programming background is necessary.

Terms: Fall | Credits 3 | Grading: A-F

Schedule for HGEN 611

August thru December || Wed, Fri 10:30 AM – 11:50 AM

Course Instructor

Timothy York, Ph.D.

York, TimothyAssociate Professor
My interests are in the application and development of statistical genetic methodology to quantify the contribution of genetic and environmental sources to complex traits, human disease and development.